CUDA系列学习（四）Parallel Task类型 与 Memory Allocation
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CUDA系列学习（四）Parallel Task类型 与 Memory Allocation
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本文為CUDA系列學習第四講，首先介紹了Parallel communication patterns的幾種形式（map, gather, scatter, stencil, transpose）, 然后復習了cuda memory model并從high level上分析怎樣寫出高效代碼，最后學習了流程控制（control flow）以及其中一個重要部分——原子操作。參考資料：udacity cs344.
(一). Parallel communication Patterns
在上一章CUDA系列學習（二）CUDA memory & variables中我們介紹了memory和variable的不同類型，本章中根據不同的memory映射方式，我們將task分為以下幾種類型：Map, Gather, Scatter, Stencil, transpose.
1.1 Map, Gather, Scatter
- Map: one input - one output
- Gather: several input - one output?
e.g image blur by average - Scatter: one input - several output?
e.g add a value to its neighbors?
(因為每個thread 將結果scatter到各個memory，所以叫scatter)
圖為Map, Gather & Scatter示意圖:
1.2 Stencil, Transpose
-
stencil: 對input中的每一個位置，?
stencil input：該點的neighborhood?
stencil output：該點value?
e.g image blur by average?
這樣也可以看出，stencil和gather很像，其實stencil是gather的一種，只不過stencil要求input必須是neighborhood而且對input的每一個元素都要操作?
圖示： - 2D stencil: (示例為兩種形式)?
? - 3D stencil:?
-
transpose?
input：matrix M?
output: M^T?
圖示： -
Matrix transpose?
-
Transpose represents in vector?
Exercise?
Q:?
看這個quiz圖，給每個藍線畫著的句子標注map/gather/scatter/stencil/transpose:?
A:四個位置分別選AECB。?
這里我最后一個選錯成B&D, 為什么不選D呢？看stencil的定義：如果是average，也應該對每一個位置都要進行average，而題目中有if(i%2)這個condition。
那么對于不同的Parallel communication Patterns需要關注哪些點呢？?
1. threads怎樣高效訪問memory？- 怎樣重用數據？?
2. threads怎樣相互交互部分結果？（通過sharing memory）這樣安全嗎？
我們將在下一節中首先回顧講過的memory model，然后結合具體問題分析闡述how to program。
(二). Programming model and Memroy model
第一講和第三講中我們講過SM與grid, block, thead的關系：各個grid, block的thread組織（gridDim，blockDim，grid shape, block shape）可以不同，分別用于執行不同kernel。?
如我們第一章所講，不同GPU有不同數量的硬件SM（streaming Multiprocessors），GPU負責將這些block分配到SMs，所有SM獨立，并行地跑。
2.1 Memory model
第二講中我們講了memroy的幾種形式，這里我們先來回顧一下memory model.
每個thread都可以訪問：?
1. 該thread獨占的local memory?
2. block內threads共享的shared memory?
3. GPU中所有threads（包括不同SM的所有threads）共享的global memory
下面復習一下，做兩個quiz。
Quiz -1 :?
Ans：選擇A,B,D?
解讀：根據定義，一個block只能run在一個SM；SM中不同blocks的threads不能cooperate
Quiz - 2 :?
Ans: 都不選~~~?
解讀：block執行時間及順序不可控；block分配到哪個SM是GPU做的事情，并非programmer能指定的；
2.2 Memory in Program
How to write Efficient Programs from high level maximize arithmetic intensity?
arithmetic intensity = calculation/memory?
即要maximize calculation per thread 并 minimize memory per thread(其實目的是minimize memory access的時間)?
方法：經常訪問的數據放在可快速訪問的memory（GPU中不同memory在硬件層的介紹參考第二章），對于剛才講的local, shared and global memory的訪問速度, 有?
local > shared >> global >> CPU memory?
所以，比如我想經常訪問一個global memory，那可以在kernel中先將該global memory variable賦值給一個shared memory variable, 然后頻繁訪問那個shared memory variable.
minimize memory access stride?
如coalesce memory access圖所示:?
如果GPU的threads訪問相鄰memory，我們稱為coalesced，如果threads間訪問memory有固定步長(蹦著走)，我們稱stripped，完全沒規律的memory訪問稱為random。訪問速度，有?
coalesced > strided > random
avoid thread divergence?
這個我們在前兩講中有過相應說明。
Exercise:
給下面這段代碼中5,6,7,8行的幾句話執行速度排序（1最快，4最慢）：
<code class="hljs r has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;"><span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span> __global__ void f(float* x, float* y, float* z){ <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">2</span> float s,t,u; <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">3</span> __shared__ float a,b,c; <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">4</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">...</span> <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">5</span> s = *x; <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">6</span> t = s; <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">7</span> a = b; <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">8</span> *y = *z; <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">9</span> }</code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li></ul>Ans: 5,6,7,8行執行速度為：3,1,2,4。
下面一節我們來看具體programming問題中的流程控制與同步。
(三). Control flow and synchronisation
3.1 program 運行順序
在講流程控制之前我們首先看一個例子，用來測試不同block的運行順序。
Demo code:
<code class="hljs vala has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;"><span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#include <stdio.h></span> <span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#define Num_block 16</span> <span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#define Num_thread 1</span>__global__ <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">void</span> print(){printf(“Num: %d\n”,blockIdx.x); }<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> main(){<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">//launch the kernel</span>print<<<Num_block, Num_thread>>>();cudaDeviceSynchronize();<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// what is the function of this sentence? - force the printf()s to flush， 不然運行時顯示不出來</span><span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">return</span> <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">0</span>; }</code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li><li style="box-sizing: border-box; padding: 0px 5px;">10</li><li style="box-sizing: border-box; padding: 0px 5px;">11</li><li style="box-sizing: border-box; padding: 0px 5px;">12</li><li style="box-sizing: border-box; padding: 0px 5px;">13</li><li style="box-sizing: border-box; padding: 0px 5px;">14</li></ul> 編譯命令：?
nvcc -arch=sm_21 -I ~/NVIDIA_GPU_Computing_SDK/C/common/inc print.cu
運行兩次結果：
可見程序執行每一次的結果都不同，也就是不同block之間的執行順序是不可控的，正如剛才quiz的ans。那么如果我們希望同步各個threads呢？
3.2 同步機制
第二章中我們在一個例子中引入并使用了同步函數syncthreads(), 即設置一個barrier，使所有threads運行到同步函數的時候stop and wait, 直到所有threads運行到此處，那么問題來了。
Exercise:?
考慮一個程序，將每個位置i的元素移到i-1的位置，需要多少個syncthreads()？?
e.g kernel中聲明如下：
Ans: 3個~
<code class="hljs cpp has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;">… <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> idx = threadIdx.x; __shared__ <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> <span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">array</span>[<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">128</span>]; <span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">array</span>[idx] = idx; __syncthreads(); <span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">//如果不加將導致array還沒賦值就被操作</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">if</span> (idx<<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">127</span>){<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> tmp = <span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">array</span>[idx];__syncthreads();<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">//如不加導致先讀后寫，數據相關</span><span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">array</span>[idx] = tmp;__syncthreads(); <span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">//如不加不能確保下面的程序訪問到正確數據</span> } … </code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li><li style="box-sizing: border-box; padding: 0px 5px;">10</li><li style="box-sizing: border-box; padding: 0px 5px;">11</li><li style="box-sizing: border-box; padding: 0px 5px;">12</li><li style="box-sizing: border-box; padding: 0px 5px;">13</li></ul>Quiz: 看下面這個程序會不會出現collision，哪里會出現collision?
<code class="hljs perl has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;"><span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1__</span>global_<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">_</span> void f(){ <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">2</span> __shared_<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">_</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">s</span>[<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1024</span>]; <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">3</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> i = threadIdx.<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">x</span>; <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">4</span> __syncthreads(); <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">5</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">s</span>[i] = <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">s</span>[i-<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>]; <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">6</span> __syncthreads(); <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">7</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">if</span>(i<span class="hljs-variable" style="color: rgb(102, 0, 102); box-sizing: border-box;">%2</span>) <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">s</span>[i] = <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">s</span>[i-<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>]; <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">8</span> __syncthreads(); <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">9</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">s</span>[i] = (<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">s</span>[i-<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>]+<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">s</span>[i+<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>])/<span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">2</span>; <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">10</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">printf</span>(“<span class="hljs-variable" style="color: rgb(102, 0, 102); box-sizing: border-box;">%d</span>\n”,<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">s</span>[i]); <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">11</span> }</code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li><li style="box-sizing: border-box; padding: 0px 5px;">10</li><li style="box-sizing: border-box; padding: 0px 5px;">11</li></ul> Ans: Collision在?
1. 第5行，如上題，應為int tmp = s[i-1]; __syncthread(); s[i] = tmp;?
2. 第9行，同理?
PS： 第7行是沒問題的，模擬一下就知道
3.3 Atomic Memory Operation
這一節中我們將要接觸到原子操作。?
首先考慮一個問題：用1000000個threads給一個長為10個元素的array做加法，希望每個thread加100000，這個代碼大家先寫寫看，很簡單，依照我們之前的方法有下面的code:
注：這里的gputimer.h請去我的資源頁面自行下載。
<code class="hljs cpp has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;"><span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#include <stdio.h></span> <span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#include "gputimer.h"</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">using</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">namespace</span> Gadgetron;<span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#define NUM_THREADS 1000000</span> <span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#define ARRAY_SIZE 10</span> <span class="hljs-preprocessor" style="color: rgb(68, 68, 68); box-sizing: border-box;">#define BLOCK_WIDTH 1000</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">void</span> print_array(<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> *<span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">array</span>, <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> size) {<span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">printf</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"{ "</span>);<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">for</span> (<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> i = <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">0</span>; i<size; i++) { <span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">printf</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"%d "</span>, <span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">array</span>[i]); }<span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">printf</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"}\n"</span>); } __global__ <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">void</span> increment_naive(<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> *g) {<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// which thread is this?</span><span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> i = blockIdx.x * blockDim.x + threadIdx.x;<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// each thread to increment consecutive elements, wrapping at ARRAY_SIZE</span>i = i % ARRAY_SIZE; g[i] = g[i] + <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>; } __global__ <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">void</span> increment_atomic(<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> *g) {<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// which thread is this?</span><span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> i = blockIdx.x * blockDim.x + threadIdx.x;<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// each thread to increment consecutive elements, wrapping at ARRAY_SIZE</span>i = i % ARRAY_SIZE; atomicAdd(&g[i], <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>); } <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> main(<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> argc,<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">char</span> **argv) { GPUTimer timer;<span class="hljs-built_in" style="color: rgb(102, 0, 102); box-sizing: border-box;">printf</span>(<span class="hljs-string" style="color: rgb(0, 136, 0); box-sizing: border-box;">"%d total threads in %d blocks writing into %d array elements\n"</span>,NUM_THREADS, NUM_THREADS / BLOCK_WIDTH, ARRAY_SIZE);<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// declare and allocate host memory</span><span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> h_array[ARRAY_SIZE];<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">const</span> <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> ARRAY_BYTES = ARRAY_SIZE * <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">sizeof</span>(<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span>);<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// declare, allocate, and zero out GPU memory</span><span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> * d_array;cudaMalloc((<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">void</span> **) &d_array, ARRAY_BYTES);cudaMemset((<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">void</span> *) d_array, <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">0</span>, ARRAY_BYTES);<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// launch the kernel - comment out one of these</span>timer.start();<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">//increment_atomic<<<NUM_THREADS/BLOCK_WIDTH, BLOCK_WIDTH>>>(d_array);</span>increment_naive<<<NUM_THREADS/BLOCK_WIDTH, BLOCK_WIDTH>>>(d_array);timer.stop();<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// copy back the array of sums from GPU and print</span>cudaMemcpy(h_array, d_array, ARRAY_BYTES, cudaMemcpyDeviceToHost);print_array(h_array, ARRAY_SIZE);<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// free GPU memory allocation and exit</span>cudaFree(d_array);<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">return</span> <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">0</span>; } </code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li><li style="box-sizing: border-box; padding: 0px 5px;">9</li><li style="box-sizing: border-box; padding: 0px 5px;">10</li><li style="box-sizing: border-box; padding: 0px 5px;">11</li><li style="box-sizing: border-box; padding: 0px 5px;">12</li><li style="box-sizing: border-box; padding: 0px 5px;">13</li><li style="box-sizing: border-box; padding: 0px 5px;">14</li><li style="box-sizing: border-box; padding: 0px 5px;">15</li><li style="box-sizing: border-box; padding: 0px 5px;">16</li><li style="box-sizing: border-box; padding: 0px 5px;">17</li><li style="box-sizing: border-box; padding: 0px 5px;">18</li><li style="box-sizing: border-box; padding: 0px 5px;">19</li><li style="box-sizing: border-box; padding: 0px 5px;">20</li><li style="box-sizing: border-box; padding: 0px 5px;">21</li><li style="box-sizing: border-box; padding: 0px 5px;">22</li><li style="box-sizing: border-box; padding: 0px 5px;">23</li><li style="box-sizing: border-box; padding: 0px 5px;">24</li><li style="box-sizing: border-box; padding: 0px 5px;">25</li><li style="box-sizing: border-box; padding: 0px 5px;">26</li><li style="box-sizing: border-box; padding: 0px 5px;">27</li><li style="box-sizing: border-box; padding: 0px 5px;">28</li><li style="box-sizing: border-box; padding: 0px 5px;">29</li><li style="box-sizing: border-box; padding: 0px 5px;">30</li><li style="box-sizing: border-box; padding: 0px 5px;">31</li><li style="box-sizing: border-box; padding: 0px 5px;">32</li><li style="box-sizing: border-box; padding: 0px 5px;">33</li><li style="box-sizing: border-box; padding: 0px 5px;">34</li><li style="box-sizing: border-box; padding: 0px 5px;">35</li><li style="box-sizing: border-box; padding: 0px 5px;">36</li><li style="box-sizing: border-box; padding: 0px 5px;">37</li><li style="box-sizing: border-box; padding: 0px 5px;">38</li><li style="box-sizing: border-box; padding: 0px 5px;">39</li><li style="box-sizing: border-box; padding: 0px 5px;">40</li><li style="box-sizing: border-box; padding: 0px 5px;">41</li><li style="box-sizing: border-box; padding: 0px 5px;">42</li><li style="box-sizing: border-box; padding: 0px 5px;">43</li><li style="box-sizing: border-box; padding: 0px 5px;">44</li><li style="box-sizing: border-box; padding: 0px 5px;">45</li><li style="box-sizing: border-box; padding: 0px 5px;">46</li><li style="box-sizing: border-box; padding: 0px 5px;">47</li><li style="box-sizing: border-box; padding: 0px 5px;">48</li><li style="box-sizing: border-box; padding: 0px 5px;">49</li><li style="box-sizing: border-box; padding: 0px 5px;">50</li><li style="box-sizing: border-box; padding: 0px 5px;">51</li><li style="box-sizing: border-box; padding: 0px 5px;">52</li><li style="box-sizing: border-box; padding: 0px 5px;">53</li><li style="box-sizing: border-box; padding: 0px 5px;">54</li><li style="box-sizing: border-box; padding: 0px 5px;">55</li><li style="box-sizing: border-box; padding: 0px 5px;">56</li><li style="box-sizing: border-box; padding: 0px 5px;">57</li><li style="box-sizing: border-box; padding: 0px 5px;">58</li></ul> 執行兩次的結果：?
可見結果里每個元素都是648/647，不符合預期100000。這是為什么呢？
看我們的kernel部分代碼，每次執行g[i] = g[i] + 1, 一個read-modify-write操作，這樣會導致許多線程讀到g[i]的value，然后慢的線程將快的線程寫結果覆蓋掉了。如何解決呢？我們引入原子操作（atomic operation）, 更改上面的kernel部分為：
<code class="hljs cs has-numbering" style="display: block; padding: 0px; color: inherit; box-sizing: border-box; font-family: 'Source Code Pro', monospace;font-size:undefined; white-space: pre; border-radius: 0px; word-wrap: normal; background: transparent;">__global__ <span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">void</span> increment_atomic(<span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> *g) {<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// which thread is this?</span><span class="hljs-keyword" style="color: rgb(0, 0, 136); box-sizing: border-box;">int</span> i = blockIdx.x * blockDim.x + threadIdx.x;<span class="hljs-comment" style="color: rgb(136, 0, 0); box-sizing: border-box;">// each thread to increment consecutive elements, wrapping at ARRAY_SIZE</span>i = i % ARRAY_SIZE; atomicAdd(&g[i], <span class="hljs-number" style="color: rgb(0, 102, 102); box-sizing: border-box;">1</span>); }</code><ul class="pre-numbering" style="box-sizing: border-box; position: absolute; width: 50px; top: 0px; left: 0px; margin: 0px; padding: 6px 0px 40px; border-right-width: 1px; border-right-style: solid; border-right-color: rgb(221, 221, 221); list-style: none; text-align: right; background-color: rgb(238, 238, 238);"><li style="box-sizing: border-box; padding: 0px 5px;">1</li><li style="box-sizing: border-box; padding: 0px 5px;">2</li><li style="box-sizing: border-box; padding: 0px 5px;">3</li><li style="box-sizing: border-box; padding: 0px 5px;">4</li><li style="box-sizing: border-box; padding: 0px 5px;">5</li><li style="box-sizing: border-box; padding: 0px 5px;">6</li><li style="box-sizing: border-box; padding: 0px 5px;">7</li><li style="box-sizing: border-box; padding: 0px 5px;">8</li></ul> 我們可以得到結果：?
可見，結果正確。那么原子操作atomicAdd用了怎樣的機制呢？——原子操作用了GPU built-in的特殊硬件，用以保證原子操作（同一時刻只能有一個thread做read-modify-write操作）
這里來看一下原子操作的limitations:?
1. only certain operations, data type（功能有限）?
2. still no ordering constraints（還是無序執行）?
3. serializes access to memory（所以慢）
(四). 總結
本節課介紹了以下內容：
-
communication patterns
- map
- gather
- scatter
- stencil
- transpose
-
gpu hardware & programming model
- SMs, threads, blocks ordering
- synchronization
- Memory model - local, global, shared memory
-
efficient GPU programming
- coalesced memory access
- faster memory for common used variable
OK~ 第三課就結束了，過兩天我把exercise上上來~ 敬請關注~.~
from:?http://blog.csdn.net/abcjennifer/article/details/43374009
總結
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